Digital cameras may be used to capture digital videos in a variety of settings. In view of the availability of expanded digital memory, users tend to capture more videos, and increasingly longer videos, as memory consumption becomes less of a concern. Increasing number and length of videos, however, results in inefficiencies in management of video libraries.
Manual review of videos to identify scenes the user finds exciting, entertaining, or otherwise interesting for view may be both time consuming, and resource intensive. For example, scrolling through multiple videos of various lengths to find such scenes burdens processors, memory, and battery of computing devices, such as mobile computing devices. Automated video processing technologies have been developed to identify scenes potentially interesting to the user. However, such video processing technologies may be resource-intensive, particularly with high-resolution, raw-format video data.
Further, after identifying an interesting scene, the user may wish to edit the scene using a digital editing environment. For example, the user may edit the scene to include effects (e.g., slow motion, zoom-in, zoom-out, color effects, and the like), which may enhance the scene, or otherwise affect user enjoyment of the scene. However, the user may undergo a trial-and-error process of adding/removing effects in different combinations, and/or with different effect attributes. Such editing processes may be time and resource intensive, thereby burdening processors, memory, and battery of computing devices, such as mobile computing devices.